A finite capacity dynamic priority queuing model

1992 ◽  
Vol 22 (4) ◽  
pp. 369-385 ◽  
Author(s):  
S. Chakravarthy
Keyword(s):  
Finite Capacity ◽  
Queuing Model ◽  
Dynamic Priority

scholarly journals Performance Analysis of D2D Underlying Cellular Networks Based on Dynamic Priority Queuing Model

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 27479-27489 ◽  
Author(s):  
Jianfang Xin ◽  
Qi Zhu ◽  
Guangjun Liang ◽  
Tianjiao Zhang
Keyword(s):  
Performance Analysis ◽  
Cellular Networks ◽  
Queuing Model ◽  
Dynamic Priority

Approximations in finite-capacity multi-server queues by Poisson arrivals

1978 ◽  
Vol 15 (4) ◽  
pp. 826-834 ◽  
Author(s):  
Shirley A. Nozaki ◽  
Sheldon M. Ross
Keyword(s):  
Service Time ◽  
Joint Distribution ◽  
Finite Capacity ◽  
Queuing Model ◽  
Average Delay ◽  
Service Distribution ◽  
Poisson Arrivals ◽  
Multi Server

An approximation for the average delay in queue of an entering customer is presented for the M/G/K queuing model with finite capacity. The approximation is obtained by means of an approximation relating a joint distribution of remaining service time to the equilibrium service distribution.

scholarly journals A novel approach for optimization in a fuzzy finite capacity queuing model with system cost and expected degree of customer satisfaction

2015 ◽  
Vol 4 (4) ◽  
pp. 487-496 ◽  
Author(s):  
Mohammad Bagher Shahin ◽  
Ali Doniavi ◽  
Maghsoud Solimanpur ◽  
Mahdi Shahin
Keyword(s):  
Customer Satisfaction ◽  
Finite Capacity ◽  
Queuing Model ◽  
System Cost ◽  
Novel Approach

Approximations in finite-capacity multi-server queues by Poisson arrivals

1978 ◽  
Vol 15 (04) ◽  
pp. 826-834 ◽  
Author(s):  
Shirley A. Nozaki ◽  
Sheldon M. Ross
Keyword(s):  
Service Time ◽  
Joint Distribution ◽  
Finite Capacity ◽  
Queuing Model ◽  
Average Delay ◽  
Service Distribution ◽  
Poisson Arrivals ◽  
Multi Server

An approximation for the average delay in queue of an entering customer is presented for the M/G/K queuing model with finite capacity. The approximation is obtained by means of an approximation relating a joint distribution of remaining service time to the equilibrium service distribution.

A FINITE CAPACITY RESEQUENCING MODEL WITH MARKOVIAN ARRIVALS

2005 ◽  
Vol 22 (03) ◽  
pp. 409-443 ◽  
Author(s):  
SRINIVAS R. CHAKRAVARTHY ◽  
STEFANKA CHUKOVA
Keyword(s):  
Steady State ◽  
Optimization Problems ◽  
Arrival Process ◽  
Finite Buffer ◽  
Finite Capacity ◽  
Departure Process ◽  
Queuing Model ◽  
Process Map ◽  
Steady State Analysis ◽  
Numerical Examples

In this paper, we consider a two-server finite capacity queuing model in which messages should leave the system in the order in which they entered the system. Messages arrive according to a Markovian arrival process (MAP) and any message finding the buffer full is considered lost. Out-of-sequence messages are stored in a (finite) buffer and may lead to blocking when a processed message cannot be placed in the buffer. The steady state analysis of the model is performed by exploiting the structure of the coefficient matrices. The departure process is characterized and two interesting optimization problems along with illustrative numerical examples are discussed.

scholarly journals Profit Optimization in SLA-Aware Cloud Services with a Finite Capacity Queuing Model

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Yi-Ju Chiang ◽  
Yen-Chieh Ouyang
Keyword(s):  
Arrival Rate ◽  
Service Level ◽  
Cloud Services ◽  
System Capacity ◽  
Optimal Decision ◽  
Cloud Provider ◽  
System Control ◽  
Finite Capacity ◽  
Queuing Model ◽  
Computing Paradigm

Cloud computing realizes a utility computing paradigm by offering shared resources through an Internet-based computing. However, how a system control can enhance profit and simultaneously satisfy the service level agreements (SLAs) has become one of the major interests for cloud providers. In this paper, a cloud server farm provided with finite capacity is modeled as anM/M/R/Kqueuing system. Revenue losses are estimated according to the system controls and impatient customer behaviors. Three important issues are solved in this paper. First, a profit function is developed in which both the system blocking loss and the user abandonment loss are evaluated in total revenue. A tradeoff between meeting system performances and reducing operating costs is conducted. Second, the effects of system capacity control and utilization on various performances of waiting time, loss probability, and final arrival rate are demonstrated. Finally, the proposed optimal profit control (OPC) policy allows a cloud provider to make the optimal decision in the number of servers and system capacity, so as to maximize profit. As compared to a system without applying the OPC policy, enhancing providers’ profit and improving system performances can be obtained.

Queuing Model Based Data Centers: A Review

2019 ◽  
Vol 123 ◽  
pp. 11-20 ◽  
Author(s):  
N. Thirupathi Rao ◽  
Debnath Bhattacharyya ◽  
S. Naga Mallik Raj
Keyword(s):  
Data Centers ◽  
Queuing Model ◽  
Model Based
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